It is generally well accepted that monitoring respiration performance provides diagnostic insight into a patient's overall health as well as specific respiratory function. Understandably, the accuracy of any diagnosis or conclusion based on respiratory performance depends upon the skill of the technician interpreting the interpretation as well, the accuracy of the information acquired, and the timeliness of the calculation of the information. Respiratory monitoring generally requires the acquisition of the breath sample and a determination of a make-up or composition of the acquired breath sample. Physiologic events, patient condition, equipment construction and operation, and ambient conditions directly affect the accuracy of the information acquired by the respiration monitoring system. Accordingly, failure to account for activities associates with these events detrimentally affects the accuracy of the information acquired and any conclusions based thereon. Furthermore, the timeliness of the respiration performance determination directly affects patient treatment determinations.
The cardiac cycle is one physiological event that can be taken into account in generating respiratory performance information. During the cardiac cycle, expansion of the chambers of the heart compresses against the lungs and generates a flow anomaly in the respiration cycle. Although the flow anomaly is internally imperceptible to most people, the flow anomaly presents a discontinuity in the respiratory flow that, if unaddressed, can lead to inaccurate interpretation of respiration performance. Other physiological conditions, such as poor lung performance, can also detrimentally affect interpretation of monitored respiration information. Flow path dead-space is another factor that must be addressed to provide an accurate determination of respiration performance. The flow path dead-spaces include patient respiration dead-spaces as well as dead-spaces associated with respiration monitoring system, or aspiration dead-spaces.
Respiration flow path dead-spaces are those portions of a respiration path that are susceptible to retaining exhalation or inhalation gases. Within a patient, the tracheal passage, mouth, and tongue can each contribute to respiration flow dead-spaces. Gases from a previous inhalation or exhalation cycle may momentarily remain in these spaces even though a subsequent inhalation or exhalation has begun. Within the monitoring equipment, the connection lines and sensor construction can each present dead-space data collection errors. That is, the lines that connect the sensor to the monitor and the sensor inserted into the respiration flow path may each retain gases associated with a previous inhalation of exhalation cycle. The accuracy of any respiration monitoring depends in part upon the monitoring systems ability to correct the respiration performance information for each of these exemplary dead-spaces.
Ambient conditions also affect the accuracy of the information acquired during respiration monitoring. For example, in an oxygen rich environment, an exhalation that includes elevated levels of oxygen would not provide an accurate indication of respiration performance if compared to respiration performance for an environment that does not include the elevated levels of oxygen. Similarly, an exhalation that includes excessive amounts of carbon dioxide provides no indication of the physiological performance if the testing environment is already rich in carbon dioxide. Accordingly, accurate respiration monitoring system must also account for deviations in the ambient test conditions.
Capnography, or the measurement of carbon dioxide in an exhalation, is commonly performed in many medical fields, including ventilated patients. Knowing the concentration of carbon dioxide as a function of time renders information about breath frequency, e.g. breaths per minute, and inspired or re-breathed levels of carbon dioxide. In some circumstances there is good agreement between the highest levels measured, often the end-tidal concentration of the carbon dioxide, and an arterial concentration, which is of value in caring for seriously compromised individuals. Understandably, such methods of comparing exhaled carbon dioxide levels to arterial carbon dioxide levels lack real-time monitoring of respiration performance.
Ascertaining an actual amount of a chemical being consumed or generated by a patient enhances the temporal or real-time monitoring and diagnosis of a patient condition. That is, monitoring both the respiration composition as well as volume enhances the diagnostic feature of a respiration monitoring system. Prior methods have relied upon collecting the exhalation gases and analyzing them sometime after the exhalation to ascertain the condition of the patient. This method, commonly referred to as the “Douglas Bag” collection method, is cumbersome, labor intensive, and discounts all of the information that can be acquired with real-time breath-by-breath data acquisition and analysis. This method is also commonly referred to as ‘indirect calorimetry’ for its indirect determination of the caloric expenditure of a patient by quantifying the carbon dioxide produced. Accordingly, it is desired to provide a respiration monitoring system that is configured to directly measure gas volumes as they are being produced or in real-time and preferably on a breath-by-breath basis.
To accomplish the measuring of gas volumes on a breath-by-breath basis, the gas concentrations as a function of time must be collected simultaneously with the flow information. Gas concentrations measured at the same location and at the same time as the flow measurement are commonly referred to as mainstream monitoring. A disadvantage of mainstream monitoring is that the monitoring is commonly performed at the location of the patient's exhaled breadth, i.e., the mouth, or as close to the site of exhalation as possible. The equipment commonly utilized for such monitoring generally tends to be large, cumbersome, and costly. Another drawback of such monitoring systems is the increase in dead-space volumes that must be overcome by a patient. Attempts at miniaturizing these devices only further increases the cost associated with these diagnostic tools. Accordingly, there is a need for a lightweight, portable respiration monitoring system with reduced dead-space volumes.
Although side-stream systems, also known as metabolic carts, address most of these issues, such systems present other drawbacks. A side-stream system draws a sample of the patient's breath and transmits it to a remote gas concentration analyzer. A side-stream system is normally capable of measuring the flow in real time. However, the acquired expiration sample must travel some distance thru lumen tubing or the like to reach the gas content analyzer. Since the gas sample is analyzed at some time after the passage of the patients flow, such side-stream systems present a temporal misalignment between the value of the respiration flow and the gas concentration values. This temporal or time wise misalignment makes side-stream systems more difficult to implement and the data acquired therefrom more difficult to interpret. Accordingly, technicians must be extensively trained in the operation and understanding of the information acquired with such systems. As such, there is also a need for a respiration monitoring system that is cost effective to manufacture, implement, and operate.
Another consideration of respiration monitoring systems is calibration of the monitoring system as well as the display of the acquired information. The calibration of known respiratory monitoring systems is a time consuming and labor intensive process. The calibration generally consists of a technician passing a known volume of a known gas several times into the monitoring system. The combination of the known gas and the relatively known volume provides operative information that provides for calibrating the monitoring system. Unfortunately, the calibration process is generally only performed at the initiation of a monitoring session, must be frequently repeated to ensure the accurate operation of the monitoring system, and does not adequately address variations in the testing environment. Additionally, such calibration generally relies heavily on the experience of the technician performing the calibration and the availability of the calibration tools such as a gas tube injector of a known volume and a known gas.
The output of known monitoring systems also presents the potential for misinterpretation. During inhalation, the monitored oxygen level should be at a maximum level and the monitored carbon dioxide level should be at a minimum, i.e. ambient conditions. During exhalation, the detected oxygen level should be at a minimum and the detected carbon dioxide level should be a maximum. The inverse relationship of the oxygen level and the carbon dioxide level across a respiration cycle as well as the dynamic function of the respiration flow is generally not temporary aligned across a respiration cycle. As shown in FIG. 1, the respiration information is generally produced with no cyclic alignment and a technician must mentally align the output to generate a real-time flow and composition of the respiratory function. FIG. 1 represents a trend plot 8 that includes a carbon dioxide trend 10 and a flow trend 12. A first ordinate 14 shows that the carbon dioxide trend 10 is always positive as indicated by abscissa 15 and ranges from a plurality of relative minimums 16 to a plurality of relative maximums 18. As discussed above, the relative maximums 18 of the carbon dioxide trend 10 reflect patient expiration whereas areas proximate relative minimums 16 reflect carbon dioxide levels associated with dead-space data acquisition and ambient carbon dioxide levels.
Flow trend 12 is indexed at second ordinate 20. Flow trend 12 repeatedly crosses abscissa 15 such that positive values indicate an inhalation and negative values indicate an exhalation. As discussed above, each exhalation, a flow associated with a negative flow trend value, should correlate to a relative maximum of the carbon dioxide trend. As indicated with the reference letters A, B, C, and D, temporally aligning the flow trend and the carbon dioxide trend requires phase shifting of flow trend 12 to the right relative to carbon dioxide trend 10. An identifier must be acquired to ensure an appropriate shift of the relative trends in determine the time-wise alignment of the flow and respiration composition information. Another lacking of known respiration monitoring systems is the ability to concurrently align a respiration flow value, a carbon dioxide concentration value, and an oxygen concentration value. Frequently, a carbon dioxide value and an oxygen value are displayed on different axis or completely different screens and therefore are not time aligned for interpretation.
Each of the drawbacks discussed above result in shortcomings in the implementation of known respiration monitoring systems. The cost and complexity of these respiration monitoring systems result in their infrequent utilization or improper interpretation of the results acquired with such systems. Furthermore, the information acquired and utilized by such systems limits the diagnostic functionality of such systems in disregarding that information that can be utilized by time aligning the variable functions of the respiration cycle and variations in operation of the monitoring system.
Accordingly, there is a need for a real-time respiratory monitoring system that is configured to align respiration flow information and respiration composition information. Furthermore, there is a need for a respiration monitoring system that is simple and efficient to manufacture and operate and one which provides concise real-time time aligned respiration information.